{smcl}
{com}{sf}{ul off}{txt}{.-}
       log:  {res}K:\Projects\IGO\IGORChecks.log
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}24 Apr 2005, 01:17:43
{txt}
{com}. do "C:\DOCUME~1\ALEXMO~1\LOCALS~1\Temp\STD01000000.tmp"
{txt}
{com}. /*Load data file first*/
. 
. /*CentMax/Min/Sum*/
. #del ;
{txt}delimiter now ;
{com}. logit disp_l1
> IGOSame ClusSame CentMax ClusSizeMax 
> smldmat smldep
> lcaprat2 allies hegdefb
> contig logdstab majpower 
> disp_spl*,
> cluster(dyadid) nolog;

{txt}Logit estimates                                   Number of obs   = {res}    149403
                                                  {txt}Wald chi2({res}16{txt})   = {res}   2161.08
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-5528.0466                 {txt}Pseudo R2       = {res}    0.3091

                           {txt}(standard errors adjusted for clustering on dyadid)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
     disp_l1 {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
     IGOSame {c |}  {res} .0311955   .0082422     3.78   0.000      .015041      .04735
    {txt}ClusSame {c |}  {res}-.1523633    .100495    -1.52   0.129    -.3493299    .0446033
     {txt}CentMax {c |}  {res}  -.00018    .000057    -3.16   0.002    -.0002916   -.0000683
 {txt}ClusSizeMax {c |}  {res} .0136113    .003801     3.58   0.000     .0061615    .0210611
     {txt}smldmat {c |}  {res}-.0713911   .0096353    -7.41   0.000    -.0902759   -.0525063
      {txt}smldep {c |}  {res}-43.72148   13.14361    -3.33   0.001    -69.48248   -17.96048
    {txt}lcaprat2 {c |}  {res}-.1804029   .0442692    -4.08   0.000    -.2671689   -.0936369
      {txt}allies {c |}  {res}-.3923381    .163704    -2.40   0.017    -.7131921   -.0714841
     {txt}hegdefb {c |}  {res} 6.717363   1.655093     4.06   0.000      3.47344    9.961286
    {txt}contigkb {c |}  {res} 1.721914   .1543898    11.15   0.000     1.419315    2.024512
    {txt}logdstab {c |}  {res}-.4292177   .0548577    -7.82   0.000    -.5367367   -.3216986
    {txt}majpower {c |}  {res} 1.896611   .1512603    12.54   0.000     1.600146    2.193076
   {txt}disp_spl0 {c |}  {res}-.6251617    .033957   -18.41   0.000    -.6917162   -.5586072
   {txt}disp_spl1 {c |}  {res}-.0065439    .000437   -14.97   0.000    -.0074004   -.0056874
   {txt}disp_spl2 {c |}  {res} .0033509   .0002465    13.59   0.000     .0028676    .0038341
   {txt}disp_spl3 {c |}  {res}-.0002622   .0000335    -7.83   0.000    -.0003278   -.0001965
       {txt}_cons {c |}  {res}-1.390837   .4568653    -3.04   0.002    -2.286277   -.4953978
{txt}{hline 13}{c BT}{hline 64}

{com}. /*No IGOSame*/
> #del ;
{txt}delimiter now ;
{com}. logit disp_l1
> ClusSame CentDif ClusSizeMax 
> smldmat smldep
> lcaprat2 allies hegdefb
> contig logdstab majpower 
> disp_spl*,
> cluster(dyadid) nolog;

{txt}Logit estimates                                   Number of obs   = {res}    149403
                                                  {txt}Wald chi2({res}15{txt})   = {res}   2175.82
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-5541.3859                 {txt}Pseudo R2       = {res}    0.3075

                           {txt}(standard errors adjusted for clustering on dyadid)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
     disp_l1 {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
    ClusSame {c |}  {res}-.1500502   .1011205    -1.48   0.138    -.3482427    .0481423
     {txt}CentDif {c |}  {res}-.0003092   .0000985    -3.14   0.002    -.0005024   -.0001161
 {txt}ClusSizeMax {c |}  {res} .0104693   .0039612     2.64   0.008     .0027056    .0182331
     {txt}smldmat {c |}  {res}-.0600519   .0097957    -6.13   0.000    -.0792511   -.0408528
      {txt}smldep {c |}  {res}-38.55175   12.17642    -3.17   0.002    -62.41709    -14.6864
    {txt}lcaprat2 {c |}  {res}-.2148723   .0422331    -5.09   0.000    -.2976477    -.132097
      {txt}allies {c |}  {res}-.2427927   .1507796    -1.61   0.107    -.5383152    .0527299
     {txt}hegdefb {c |}  {res} 10.01614   1.716307     5.84   0.000     6.652244    13.38004
    {txt}contigkb {c |}  {res} 1.737134   .1591088    10.92   0.000     1.425287    2.048982
    {txt}logdstab {c |}  {res}-.4791934   .0573551    -8.35   0.000    -.5916074   -.3667794
    {txt}majpower {c |}  {res} 2.003802   .1553528    12.90   0.000     1.699316    2.308288
   {txt}disp_spl0 {c |}  {res}-.6231151   .0342468   -18.19   0.000    -.6902376   -.5559926
   {txt}disp_spl1 {c |}  {res}-.0066255   .0004389   -15.10   0.000    -.0074857   -.0057653
   {txt}disp_spl2 {c |}  {res} .0034067   .0002456    13.87   0.000     .0029253     .003888
   {txt}disp_spl3 {c |}  {res}-.0002725   .0000322    -8.47   0.000    -.0003356   -.0002094
       {txt}_cons {c |}  {res}-.7375009   .4823177    -1.53   0.126    -1.682826    .2078245
{txt}{hline 13}{c BT}{hline 64}

{com}. /*6 clusters instead of variable*/
> #del ;
{txt}delimiter now ;
{com}. logit disp_l1
> IGOSame H6ClusSame CentDif H6ClusSizeMax 
> smldmat smldep
> lcaprat2 allies hegdefb
> contig logdstab majpower 
> disp_spl*,
> cluster(dyadid) nolog;

{txt}Logit estimates                                   Number of obs   = {res}    149403
                                                  {txt}Wald chi2({res}16{txt})   = {res}   2179.20
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-5529.3585                 {txt}Pseudo R2       = {res}    0.3090

                           {txt}(standard errors adjusted for clustering on dyadid)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
     disp_l1 {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
     IGOSame {c |}  {res} .0151786   .0052457     2.89   0.004     .0048971    .0254601
  {txt}H6ClusSame {c |}  {res} -.022223   .0959337    -0.23   0.817    -.2102496    .1658037
     {txt}CentDif {c |}  {res}-.0002949   .0000998    -2.96   0.003    -.0004904   -.0000993
{txt}H6ClusSize~x {c |}  {res} .0126976   .0038136     3.33   0.001     .0052232    .0201721
     {txt}smldmat {c |}  {res}-.0662909   .0095131    -6.97   0.000    -.0849363   -.0476456
      {txt}smldep {c |}  {res}-42.68459   12.55476    -3.40   0.001    -67.29146   -18.07772
    {txt}lcaprat2 {c |}  {res}-.1884019   .0436904    -4.31   0.000    -.2740336   -.1027702
      {txt}allies {c |}  {res}-.3908018   .1610883    -2.43   0.015     -.706529   -.0750745
     {txt}hegdefb {c |}  {res} 8.034728    1.72359     4.66   0.000     4.656553     11.4129
    {txt}contigkb {c |}  {res} 1.745219   .1564755    11.15   0.000     1.438532    2.051905
    {txt}logdstab {c |}  {res}-.4472867   .0551076    -8.12   0.000    -.5552955   -.3392779
    {txt}majpower {c |}  {res} 1.997606   .1511695    13.21   0.000     1.701319    2.293893
   {txt}disp_spl0 {c |}  {res}-.6231203   .0339365   -18.36   0.000    -.6896346    -.556606
   {txt}disp_spl1 {c |}  {res}-.0064658   .0004333   -14.92   0.000    -.0073151   -.0056164
   {txt}disp_spl2 {c |}  {res} .0032966   .0002437    13.53   0.000     .0028191    .0037742
   {txt}disp_spl3 {c |}  {res}-.0002516   .0000328    -7.67   0.000    -.0003158   -.0001873
       {txt}_cons {c |}  {res}-1.299074   .4488405    -2.89   0.004    -2.178785   -.4193631
{txt}{hline 13}{c BT}{hline 64}

{com}. /*HDist instead of ClusSame*/
> #del ;
{txt}delimiter now ;
{com}. logit disp_l1
> IGOSame HDist CentDif ClusSizeMax 
> smldmat smldep
> lcaprat2 allies hegdefb
> contig logdstab majpower 
> disp_spl*,
> cluster(dyadid) nolog;

{txt}Logit estimates                                   Number of obs   = {res}    149403
                                                  {txt}Wald chi2({res}16{txt})   = {res}   2221.65
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-5529.0128                 {txt}Pseudo R2       = {res}    0.3090

                           {txt}(standard errors adjusted for clustering on dyadid)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
     disp_l1 {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
     IGOSame {c |}  {res} .0138153   .0053189     2.60   0.009     .0033904    .0242402
       {txt}HDist {c |}  {res}-.2613046   .4310718    -0.61   0.544     -1.10619    .5835806
     {txt}CentDif {c |}  {res}-.0002392    .000118    -2.03   0.043    -.0004705   -8.04e-06
 {txt}ClusSizeMax {c |}  {res} .0127481   .0038182     3.34   0.001     .0052645    .0202316
     {txt}smldmat {c |}  {res}-.0654029   .0094472    -6.92   0.000    -.0839191   -.0468867
      {txt}smldep {c |}  {res}-43.01772   12.50826    -3.44   0.001    -67.53346   -18.50199
    {txt}lcaprat2 {c |}  {res}-.1880639   .0436215    -4.31   0.000    -.2735606   -.1025673
      {txt}allies {c |}  {res}-.3976402   .1590249    -2.50   0.012    -.7093232   -.0859571
     {txt}hegdefb {c |}  {res} 7.890564   1.722506     4.58   0.000     4.514514    11.26661
    {txt}contigkb {c |}  {res} 1.750224   .1557355    11.24   0.000     1.444988     2.05546
    {txt}logdstab {c |}  {res}-.4412176    .055917    -7.89   0.000    -.5508128   -.3316223
    {txt}majpower {c |}  {res} 2.013296   .1547695    13.01   0.000     1.709953    2.316638
   {txt}disp_spl0 {c |}  {res}-.6231658   .0339538   -18.35   0.000    -.6897141   -.5566176
   {txt}disp_spl1 {c |}  {res}-.0064648   .0004334   -14.92   0.000    -.0073142   -.0056155
   {txt}disp_spl2 {c |}  {res} .0032957   .0002435    13.53   0.000     .0028184    .0037729
   {txt}disp_spl3 {c |}  {res}-.0002513   .0000327    -7.68   0.000    -.0003154   -.0001872
       {txt}_cons {c |}  {res}-1.281403   .4417184    -2.90   0.004    -2.147155   -.4156506
{txt}{hline 13}{c BT}{hline 64}

{com}. /*EVCentDif instead of CentDif*/
> #del ;
{txt}delimiter now ;
{com}. logit disp_l1
> IGOSame ClusSame EVCentDif ClusSizeMax 
> smldmat smldep
> lcaprat2 allies hegdefb
> contig logdstab majpower 
> disp_spl*,
> cluster(dyadid) nolog;

{txt}Logit estimates                                   Number of obs   = {res}    149403
                                                  {txt}Wald chi2({res}16{txt})   = {res}   2267.48
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-5537.3917                 {txt}Pseudo R2       = {res}    0.3080

                           {txt}(standard errors adjusted for clustering on dyadid)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
     disp_l1 {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
     IGOSame {c |}  {res} .0113677   .0052824     2.15   0.031     .0010143    .0217211
    {txt}ClusSame {c |}  {res}-.0168055   .1023483    -0.16   0.870    -.2174046    .1837935
   {txt}EVCentDif {c |}  {res}-3.747019   2.462849    -1.52   0.128    -8.574114    1.080076
 {txt}ClusSizeMax {c |}  {res} .0125755   .0037363     3.37   0.001     .0052526    .0198985
     {txt}smldmat {c |}  {res} -.061498    .009319    -6.60   0.000     -.079763   -.0432331
      {txt}smldep {c |}  {res}-41.61083   12.36721    -3.36   0.001    -65.85011   -17.37155
    {txt}lcaprat2 {c |}  {res}-.2035096   .0419922    -4.85   0.000    -.2858129   -.1212064
      {txt}allies {c |}  {res}-.3420553   .1586332    -2.16   0.031    -.6529707   -.0311398
     {txt}hegdefb {c |}  {res} 6.751467   1.715301     3.94   0.000      3.38954    10.11339
    {txt}contigkb {c |}  {res} 1.774255    .153711    11.54   0.000     1.472987    2.075523
    {txt}logdstab {c |}  {res}-.4496977   .0561535    -8.01   0.000    -.5597566   -.3396388
    {txt}majpower {c |}  {res} 2.016558   .1520708    13.26   0.000     1.718505    2.314611
   {txt}disp_spl0 {c |}  {res}-.6206721   .0341103   -18.20   0.000    -.6875271   -.5538171
   {txt}disp_spl1 {c |}  {res}-.0064351   .0004339   -14.83   0.000    -.0072854   -.0055847
   {txt}disp_spl2 {c |}  {res} .0032777   .0002437    13.45   0.000     .0028001    .0037554
   {txt}disp_spl3 {c |}  {res}-.0002484   .0000327    -7.59   0.000    -.0003126   -.0001843
       {txt}_cons {c |}  {res}-1.190281   .4611582    -2.58   0.010    -2.094135   -.2864276
{txt}{hline 13}{c BT}{hline 64}

{com}. /*Euclidean Metric instead of Hamming*/
> #del ;
{txt}delimiter now ;
{com}. logit disp_l1
> IGOSame ENClusSame CentDif ENClusSizeMax 
> smldmat smldep
> lcaprat2 allies hegdefb
> contig logdstab majpower 
> disp_spl*,
> cluster(dyadid) nolog;

{txt}Logit estimates                                   Number of obs   = {res}    149403
                                                  {txt}Wald chi2({res}16{txt})   = {res}   2224.98
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-5531.1959                 {txt}Pseudo R2       = {res}    0.3087

                           {txt}(standard errors adjusted for clustering on dyadid)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
     disp_l1 {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
     IGOSame {c |}  {res} .0138937   .0051558     2.69   0.007     .0037885     .023999
  {txt}ENClusSame {c |}  {res}-.2334596   .0917694    -2.54   0.011    -.4133243    -.053595
     {txt}CentDif {c |}  {res}-.0003704   .0001027    -3.61   0.000    -.0005716   -.0001691
{txt}ENClusSize~x {c |}  {res} .0011421   .0040132     0.28   0.776    -.0067236    .0090079
     {txt}smldmat {c |}  {res}-.0660212   .0093545    -7.06   0.000    -.0843556   -.0476868
      {txt}smldep {c |}  {res}-42.72556   12.65032    -3.38   0.001    -67.51973   -17.93138
    {txt}lcaprat2 {c |}  {res}-.1868846   .0436443    -4.28   0.000    -.2724258   -.1013434
      {txt}allies {c |}  {res}-.3558225   .1590315    -2.24   0.025    -.6675185   -.0441265
     {txt}hegdefb {c |}  {res}  8.63142   1.698422     5.08   0.000     5.302575    11.96026
    {txt}contigkb {c |}  {res} 1.743785   .1561303    11.17   0.000     1.437775    2.049794
    {txt}logdstab {c |}  {res}-.4535389     .05551    -8.17   0.000    -.5623365   -.3447413
    {txt}majpower {c |}  {res} 1.963924   .1539013    12.76   0.000     1.662283    2.265565
   {txt}disp_spl0 {c |}  {res}-.6236598   .0338058   -18.45   0.000     -.689918   -.5574015
   {txt}disp_spl1 {c |}  {res}-.0064866   .0004341   -14.94   0.000    -.0073374   -.0056358
   {txt}disp_spl2 {c |}  {res} .0033102   .0002444    13.54   0.000     .0028311    .0037893
   {txt}disp_spl3 {c |}  {res}-.0002536    .000033    -7.70   0.000    -.0003182    -.000189
       {txt}_cons {c |}  {res}-.7931818   .4649988    -1.71   0.088    -1.704563    .1181991
{txt}{hline 13}{c BT}{hline 64}

{com}. /*Great Power IGOs*/
> #del ;
{txt}delimiter now ;
{com}. logit disp_l1 
> GP1IGOSame GP1ClusSame GP1CentDif GP1ClusSizeMax
> smldmat smldep
> lcaprat2 allies hegdefb 
> contig logdstab majpower
> disp_spl*,
> cluster(dyadid) nolog;

{txt}Logit estimates                                   Number of obs   = {res}    149403
                                                  {txt}Wald chi2({res}16{txt})   = {res}   2244.49
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res} -5518.942                 {txt}Pseudo R2       = {res}    0.3103

                           {txt}(standard errors adjusted for clustering on dyadid)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
     disp_l1 {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
  GP1IGOSame {c |}  {res} .0141084   .0056718     2.49   0.013     .0029918    .0252249
 {txt}GP1ClusSame {c |}  {res}-.1434043   .1062183    -1.35   0.177    -.3515884    .0647797
  {txt}GP1CentDif {c |}  {res}-.0003592    .000105    -3.42   0.001     -.000565   -.0001533
{txt}GP1ClusSiz~x {c |}  {res}  .013761   .0036333     3.79   0.000     .0066399    .0208821
     {txt}smldmat {c |}  {res}-.0642683   .0091406    -7.03   0.000    -.0821837    -.046353
      {txt}smldep {c |}  {res}-40.45386   12.64219    -3.20   0.001     -65.2321   -15.67562
    {txt}lcaprat2 {c |}  {res}-.1942151   .0436553    -4.45   0.000    -.2797779   -.1086523
      {txt}allies {c |}  {res}-.3754137   .1554319    -2.42   0.016    -.6800546   -.0707728
     {txt}hegdefb {c |}  {res}  7.81103   1.842256     4.24   0.000     4.200274    11.42179
    {txt}contigkb {c |}  {res} 1.752617    .156596    11.19   0.000     1.445694    2.059539
    {txt}logdstab {c |}  {res}-.4725478   .0569618    -8.30   0.000    -.5841909   -.3609047
    {txt}majpower {c |}  {res} 2.035394   .1580969    12.87   0.000      1.72553    2.345258
   {txt}disp_spl0 {c |}  {res}-.6202042   .0338927   -18.30   0.000    -.6866326   -.5537758
   {txt}disp_spl1 {c |}  {res}-.0064388   .0004338   -14.84   0.000     -.007289   -.0055887
   {txt}disp_spl2 {c |}  {res} .0032837   .0002443    13.44   0.000     .0028049    .0037624
   {txt}disp_spl3 {c |}  {res}-.0002509    .000033    -7.60   0.000    -.0003155   -.0001862
       {txt}_cons {c |}  {res}-1.091587   .4727695    -2.31   0.021    -2.018198   -.1649754
{txt}{hline 13}{c BT}{hline 64}

{com}. /*Relative IGO measure*/
> #del ;
{txt}delimiter now ;
{com}. logit disp_l1 
> IGOrl ClusSame CentDif ClusSizeMax
> smldmat smldep
> lcaprat2 allies hegdefb 
> contig logdstab majpower 
> disp_spl*,
> cluster(dyadid) nolog;

{txt}Logit estimates                                   Number of obs   = {res}    149403
                                                  {txt}Wald chi2({res}16{txt})   = {res}   2165.09
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-5538.6351                 {txt}Pseudo R2       = {res}    0.3078

                           {txt}(standard errors adjusted for clustering on dyadid)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
     disp_l1 {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
       IGOrl {c |}  {res}  .087345   .0704312     1.24   0.215    -.0506975    .2253876
    {txt}ClusSame {c |}  {res}-.1843766   .1029884    -1.79   0.073    -.3862301    .0174769
     {txt}CentDif {c |}  {res}-.0002848   .0000986    -2.89   0.004    -.0004781   -.0000915
 {txt}ClusSizeMax {c |}  {res} .0120099   .0037828     3.17   0.001     .0045957    .0194241
     {txt}smldmat {c |}  {res} -.063174   .0092146    -6.86   0.000    -.0812343   -.0451138
      {txt}smldep {c |}  {res}-43.10473   14.06285    -3.07   0.002    -70.66742   -15.54204
    {txt}lcaprat2 {c |}  {res}-.1984532   .0466245    -4.26   0.000    -.2898356   -.1070708
      {txt}allies {c |}  {res}-.2777242     .15572    -1.78   0.075    -.5829298    .0274814
     {txt}hegdefb {c |}  {res} 9.491738   1.681986     5.64   0.000     6.195106    12.78837
    {txt}contigkb {c |}  {res} 1.736459    .157969    10.99   0.000     1.426846    2.046073
    {txt}logdstab {c |}  {res}-.4612312   .0576945    -7.99   0.000    -.5743103   -.3481521
    {txt}majpower {c |}  {res} 1.949982   .1682345    11.59   0.000     1.620249    2.279716
   {txt}disp_spl0 {c |}  {res}-.6255064   .0344908   -18.14   0.000    -.6931071   -.5579056
   {txt}disp_spl1 {c |}  {res}-.0065981   .0004368   -15.10   0.000    -.0074543   -.0057419
   {txt}disp_spl2 {c |}  {res} .0033838   .0002447    13.83   0.000     .0029043    .0038634
   {txt}disp_spl3 {c |}  {res} -.000267   .0000324    -8.23   0.000    -.0003306   -.0002034
       {txt}_cons {c |}  {res}-.9429492   .4781449    -1.97   0.049    -1.880096   -.0058024
{txt}{hline 13}{c BT}{hline 64}

{com}. /*S - interest similarity*/
> #del ;
{txt}delimiter now ;
{com}. logit disp_l1 
> IGOSame ClusSame CentDif ClusSizeMax
> s_un_glo
> smldmat smldep
> lcaprat2 allies hegdefb 
> contig logdstab majpower 
> disp_spl*,
> cluster(dyadid) nolog;

{txt}Logit estimates                                   Number of obs   = {res}    149403
                                                  {txt}Wald chi2({res}17{txt})   = {res}   2188.61
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res} -5526.765                 {txt}Pseudo R2       = {res}    0.3093

                           {txt}(standard errors adjusted for clustering on dyadid)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
     disp_l1 {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
     IGOSame {c |}  {res} .0152141   .0051634     2.95   0.003     .0050941    .0253341
    {txt}ClusSame {c |}  {res}-.1692127   .1021401    -1.66   0.098    -.3694036    .0309783
     {txt}CentDif {c |}  {res}-.0003561   .0001033    -3.45   0.001    -.0005585   -.0001536
 {txt}ClusSizeMax {c |}  {res} .0116988   .0038033     3.08   0.002     .0042444    .0191532
    {txt}s_un_glo {c |}  {res} .1823281   .4305526     0.42   0.672    -.6615395    1.026196
     {txt}smldmat {c |}  {res}-.0655815   .0093715    -7.00   0.000    -.0839493   -.0472138
      {txt}smldep {c |}  {res}-41.87066   12.57497    -3.33   0.001    -66.51714   -17.22417
    {txt}lcaprat2 {c |}  {res}-.1892017   .0435739    -4.34   0.000    -.2746049   -.1037985
      {txt}allies {c |}  {res}-.3869875   .1710519    -2.26   0.024    -.7222431   -.0517319
     {txt}hegdefb {c |}  {res} 8.230991   1.939037     4.24   0.000     4.430549    12.03143
    {txt}contigkb {c |}  {res} 1.744481     .15656    11.14   0.000      1.43763    2.051333
    {txt}logdstab {c |}  {res}-.4513894    .055599    -8.12   0.000    -.5603614   -.3424174
    {txt}majpower {c |}  {res} 2.021124   .1554403    13.00   0.000     1.716466    2.325781
   {txt}disp_spl0 {c |}  {res}-.6228146   .0339518   -18.34   0.000    -.6893588   -.5562704
   {txt}disp_spl1 {c |}  {res}-.0064637   .0004336   -14.91   0.000    -.0073136   -.0056139
   {txt}disp_spl2 {c |}  {res} .0032953   .0002437    13.52   0.000     .0028177    .0037729
   {txt}disp_spl3 {c |}  {res}-.0002513   .0000327    -7.67   0.000    -.0003154   -.0001871
       {txt}_cons {c |}  {res}-1.313348    .629536    -2.09   0.037    -2.547216   -.0794801
{txt}{hline 13}{c BT}{hline 64}

{com}. /*Check multicollinearity*/
> #del ;
{txt}delimiter now ;
{com}. correl
> IGOSame ClusSame CentDif ClusSizeMax
> s_un_glo
> smldmat smldep 
> lcaprat2 allies hegdefb   
> contig logdstab majpower;
{txt}(obs=149403)

             {c |}  IGOSame ClusSame  CentDif ClusSi~x s_un_glo  smldmat   smldep
{hline 13}{c +}{hline 63}
     IGOSame {c |}{res}   1.0000
    {txt}ClusSame {c |}{res}   0.1685   1.0000
     {txt}CentDif {c |}{res}  -0.0217  -0.4330   1.0000
 {txt}ClusSizeMax {c |}{res}  -0.1362  -0.1537   0.1124   1.0000
    {txt}s_un_glo {c |}{res}  -0.0321   0.2695  -0.1251  -0.0074   1.0000
     {txt}smldmat {c |}{res}   0.2345   0.1181  -0.0660  -0.1805  -0.0181   1.0000
      {txt}smldep {c |}{res}   0.2170   0.1658  -0.1006  -0.1108   0.0710   0.1661   1.0000
    {txt}lcaprat2 {c |}{res}  -0.1673  -0.1616   0.2504   0.0710  -0.1345   0.0078  -0.1166
      {txt}allies {c |}{res}   0.3509   0.3140  -0.1018  -0.0119   0.2696   0.0137   0.1030
     {txt}hegdefb {c |}{res}   0.3190  -0.1111   0.1760   0.1627  -0.2811   0.0467  -0.0505
    {txt}contigkb {c |}{res}   0.1089   0.1924  -0.1112  -0.0763   0.0988   0.0469   0.2715
    {txt}logdstab {c |}{res}  -0.2768  -0.3184   0.1104   0.1101  -0.2607  -0.0113  -0.3106
    {txt}majpower {c |}{res}  -0.0412   0.0267  -0.0007  -0.0959  -0.2143   0.0649   0.0781

             {txt}{c |} lcaprat2   allies  hegdefb contigkb logdstab majpower
{hline 13}{c +}{hline 54}
    lcaprat2 {c |}{res}   1.0000
      {txt}allies {c |}{res}  -0.0532   1.0000
     {txt}hegdefb {c |}{res}   0.0318   0.1359   1.0000
    {txt}contigkb {c |}{res}  -0.0276   0.2331  -0.0462   1.0000
    {txt}logdstab {c |}{res}   0.1449  -0.3641   0.0345  -0.4592   1.0000
    {txt}majpower {c |}{res}   0.3818   0.0193  -0.1057   0.1813  -0.0358   1.0000

{txt}
{com}. 
{txt}end of do-file

{com}. log close
       {txt}log:  {res}K:\Projects\IGO\IGORChecks.log
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}24 Apr 2005, 01:18:21
{txt}{.-}
{smcl}
{txt}{sf}{ul off}